Air quality monitoring device and system

Abstract

An improved air quality monitoring device provides accurate and reliable predictions regarding likelihood for microbial growth on building walls. The present invention comprises a housing adapted to affix the device to a building wall, a first sensor array placed in close proximity to the wall, a second sensor array and a processing means operatively connected to the first sensor array and the second sensor array. The first sensor array provides inputs such as relative humidity at the surface of the wall, the wall temperature and wall pressure. The second sensor array provides inputs such as relative humidity, temperature pressure and quality of ambient air. Using inputs from the first sensor array and the second sensor array, the processing means generates an output representative of the likelihood of microbial growth and the likelihood that the wall moisture is caused by condensation. A system of networked monitoring devices is also described.

1 . An air quality monitoring device ( 110 ) comprising:
 a housing ( 101 ) configured to affix the device to an interior space of a wall ( 105 ), the housing ( 101 ) having a rear plate ( 101   a ) placed in contact with the wall ( 105 ) and a front plate ( 101   b ) disposed adjacent to the rear plate ( 101   a );   a first sensor array ( 103 ) mounted on the rear plate ( 101   a ), the first sensor array ( 103 ) provides a plurality of output signals representative of at least one of relative humidity at the wall surface, wall temperature and wall pressure;   a second sensor array ( 104 ) mounted on the front plate  101   b , the second sensor array ( 104 ) provides a plurality of output signals representative of at least one of ambient air temperature, ambient air pressure, ambient air quality and ambient air relative humidity; and   a processor means disposed within the housing ( 101 ) and operatively connected to the first sensor array ( 103 ) and the second sensor array ( 104 ) wherein the processor is configured to detect or predict a microbial or mold growth on the wall.   
     
     
         2 . The air quality monitoring device as claimed in  claim 1 , wherein the first sensor array ( 103 ) comprises a plurality of pressure sensors, temperature sensors and humidity sensors. 
     
     
         3 . The air quality monitoring device as claimed in  claim 1 , wherein the second sensor array ( 104 ) comprises a plurality of pressure sensors, temperature sensors, humidity sensors, carbon dioxide sensors and volatile organic compound sensors. 
     
     
         4 . The air quality monitoring device as claimed in  claim 1  wherein the second sensor array ( 104 ) is configured to measure the wall temperature, and the processor calculates when the wall temperature falls below a dewpoint condensation occurs, the device is configured to correlate condensation with equilibrium relative humidity, such that the degree to which wall moisture is driven by condensation can be ascertained. 
     
     
         5 . The air quality monitoring device as claimed in  claim 1 , wherein the device further comprises a thermal camera. 
     
     
         6 . The air quality monitoring device as claimed in  claim 1 , wherein the processing means comprises a long range (LoRa) 868 MHz RFM95 communication module. 
     
     
         7 . The air quality monitoring device as claimed in  claim 1 , wherein the rear plate ( 101   a ) has formed on it at least one through-hole and wherein the first sensor ( 103 ) array is mounted concentric to the through-hole. 
     
     
         8 . The air quality monitoring device as claimed in  claim 1 , wherein the front plate ( 101   b ) has formed on it at least one through-hole and wherein the second sensor array ( 104 ) is concentric to the through hole. 
     
     
         9 . The air quality monitoring device as claimed in  claim 1  wherein the rear plate ( 101   a ) comprises an airtight seal capturing a volume of air behind the device, said captured volume of air is in both thermal and moisture equilibrium with the wall ( 105 ). 
     
     
         10 . The air quality monitoring device as claimed in  claim 9  wherein the seal comprises a polyurethane gel gasket positioned between the rear plate ( 101   a ) and the mounting surface to ensure the integrity of the airtight seal. 
     
     
         11 . The air quality monitoring device as claimed in  claim 1  comprising a putty compound positioned to ensure that the wall humidity sensor is isolated from the rest of the device and forms an airtight seal into the volume of air encapsulated by the device and gasket at the wall. 
     
     
         12 . An air quality monitoring system comprising a plurality of monitoring devices ( 110   a ,  110   b ,  110   c  &  110   d ) as claimed in any preceding claim, wherein each monitoring device is configured with bi-directional communication to send and receive information, the monitoring system comprising a computing device ( 111 ) adapted to:
 send and receive information to and from each monitoring device ( 110   a ,  110   b ,  110   c  &  110   d ); 
 a module configured to collect and store the received data from at least one monitoring device; 
 a module to receive contextual data from one or more sources ( 112 ); 
 processing the received data from the monitoring devices ( 110   a ,  110   b ,  110   c  &  110   d ) and contextual data from at least one source ( 112 ); and 
 outputting a prediction data for a time when mold or other bacteria will form in the vicinity of a monitoring device. 
 
     
     
         13 . The air quality monitoring system of  claim 12  where the one or more sources comprises one or more of the following: a local weather source; a home heating source associated with a monitoring device location; a database source of stored historical data; a ventilation source or an air conditioning source. 
     
     
         14 . The air quality monitoring system of  claim 12  wherein a machine learning algorithm is configured to output the prediction data for a time when mold or other bacteria will form. 
     
     
         15 . The air quality monitoring system as claimed in  claim 14  wherein the machine learning algorithm receives inputs from at least one monitoring device and contextual data from one or more sources. 
     
     
         16 . The air quality monitoring system as claimed  claim 12  wherein the processor is configured, on generation of the prediction data, to generate a control signal to at least one source to control the ambient temperature conditions in the vicinity of a known monitoring device location.